Reconfigurable intelligent surface (RIS) has the potential to shape the wireless channel into an intelligent programmable wireless propagation environment. RIS-assisted millimeter wave (mmWave) technology is considered as a potential technology for sixth generation (6G) wireless communications. In this article, an RIS-assisted mmWave system is considered, and the corresponding physics-based channel model under the parabolic wavefront assumption, which is a second-order approximation to the spherical wavefront assumption, is established. Based on the parabolic wavefront assumption, the approximate closed-form expression of the direction-dependent Rayleigh distance is derived, which is a supplement to the classical Rayleigh distance. Also, the RIS reflection phase, consisting of a conventional far-field reflection phase and an addition near-field reflection phase, is obtained. The far-field phase compensates the phase variations from the mismatch in the azimuth and elevation angles, and the near-field phase compensates the phase variations caused by the distance differences from the transmitter/receiver to different RIS unit cells. Based on the conventional far-field reflection phase and the designed reflection phase, the received signal power is explored, and the approximate expressions are also obtained by using the Fresnel functions, which are validated by using numerical results. In addition, the numerical results show that the mmWave channel model under parabolic wavefront assumption and the corresponding near-field reflection phases are necessary to explore the RIS-assisted mmWave communication systems.

To effectively capture the inherent near-field effects and spatial non-stationarity across extremely large antenna arrays (ELAAs), this letter develops a novel analytical channel model tailored for extremely large-scale multiple-input multiple-output (XL-MIMO) systems. In the proposed framework, spatial non-stationarity is first characterized using a 0-1 diagonal matrix, after which the composite XL-MIMO channel matrix is formulated as a linear combination of structured matrix components. Leveraging this representation, we perform a comprehensive performance analysis, evaluating key metrics including the downlink ergodic capacity, an efficiently computable upper bound derived from eigenvalue matrix, and the symbol error probability (SEP). The analysis demonstrates that the proposed scheme not only achieves performance comparable to benchmark methods but also substantially reduces computational complexity. Furthermore, the analysis reveals a pronounced performance degradation in the presence of increasing channel estimation errors.

In the intelligent reflecting surface (IRS) aided near-field systems, the IRS reflection phases, influenced by the coupling between the IRS units, significantly affect the performance. To improve the performance gains of near-field systems, the channel models based on IRS partitioning scheme are proposed for air-to-ground (A2G) millimeter-wave (mmWave) systems. The corresponding IRS reflection phases are designed, consisting of both the IRS unit-dependent reflection phases and the sub-surface-dependent reflection phases. The designed reflection phases not only compensate for phase variations introduced by the mismatches in the azimuth and elevation angles of IRS units but also for the phase variations due to the existence of distance differences from transceiver to the centers of sub-surfaces. Using the proposed partitioning scheme, the influence of the coupling between the IRS units on the reflection phase can be effectively mitigated. To further explore the impact of the IRS partitioning scheme on performance, a power leakage ratio , which is defined as the ratio of the leakage power using the partitioning scheme to the total received signal power, is introduced. Numerical results show that the received signal power of the proposed channel model matches that of the near-field model using the ideal reflection phases very well.

Millimeter wave (mmWave) communication and intelligent reflecting surface (IRS) are both promising solutions for the next generation of wireless communication technology. In this paper, the near-field channel models based on the spherical wave assumption and parabolic wave assumption are proposed for double-IRS assistedmmWavecommunicationsystemswheretheparabolicwavemodelservesasan approximation of the spherical wave model. Under the parabolic wave assumption, the directional-dependant rayleigh distances and near-field reflection phases are investigated, and explicit expressions for the normalized array gains and path power gains are obtained using the sine integral. Based on the obtained path power gains, the suboptimal IRS rotation angles are also explored. We first consider the range limits of the activation conditions for the rotation angles, and then take the derivative of the explicit expression for the amplitude of IRS-assisted link to obtain the suboptimal rotation angles for different links. Using the designed near-field reflection phases, the approximateachievablerateisobtainedandverifiedbynumericalresultsFromtheseresultsaninteresting finding emerges: underreasonableIRSdimensionstheperformancegainsoftwoIRSsworkingnoncooperativelyaresignificantlygreater than those of two IRSs working together. In conclusion, this work highlights the importance of IRS rotation angles and the intrinsic nature of double-IRS assisted communications.

This paper develops a physically consistent precoding framework for extremely large antenna arrays (ELAAs), incorporating structural mutual coupling through a two-dimensional impedance network. To maintain scalability, we introduce a Neumann series approximation for the inverse coupling operator. Our analysis reveals that coupling-aware received power maximization reduces to a Hermitian rank-one quadratic form, whose optimum aligns with the dominant eigendirection of the effective coupling-shaped channel. This result indicates that both eigen-decomposition-based optimization and coupling-aware maximum ratio transmission (MRT) enhance power efficiency under mutual coupling, with the eigenmode design achieving superior performance. In addition, we further extend the analysis from the free-space path to the multipath scenario, demonstrating the robustness and adaptability of the proposed method under practical propagation conditions. Simulations confirm that structural coupling severely degrades conventional MRT, whereas the proposed eigenmode method with Neumann approximated coupling attains the highest received power among all considered schemes. The framework is interpretable, numerically stable, and readily implementable, offering practical guidance for energy-efficient near-field beamforming on ultra-large apertures.

Reconfigurable intelligent surfaces (RISs) have attracted significant attention due to their capability of establishing virtual line-of-sight (VLoS) links. This article proposes a channel model for RIS-assisted millimeter wave (mmWave) communication systems that incorporates the effective aperture (EA) of RIS elements, the horizontal and vertical rotation angles of the RIS, the servomechanism limitations associated with these rotation angles, and the activation criteria to constrain the feasible range of these rotation angles. To enhance the system performance, we jointly optimize the horizontal and vertical rotation angles of the RIS with the objective of maximizing the signal-to-noise ratio (SNR) based on the proposed model. An alternating optimization (AO) algorithm is developed to solve this problem efficiently. Specifically, the original optimization problem is decomposed into two subproblems corresponding to independent optimization of the horizontal and vertical angles, and closed-form optimal solutions are derived for each subproblem. Updating iteratively these closed-form solutions yields suboptimal horizontal and vertical rotation angles for the RIS. Moreover, a global optimal solution of closed-form to the original optimization problem is derived for the special case where the base station (BS) is positioned directly in front of the RIS. Numerical results demonstrate that the suboptimal rotation angles obtained by the AO algorithm closely approximate the optimal solutions. Furthermore, the proposed AO algorithm, which jointly optimizes both rotation angles, significantly outperforms the methods that individually optimize either the horizontal or vertical angle.